Collaborative Medical Delivery Service with UAVs and Human Couriers

Pengfu Wan, Gangyan Xu, Saijun Shao

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

Abstract

Unmanned Aerial Vehicle (UAV) has been widely adopted in logistics systems with improved flexibility, efficiency, and lowered cost. However, limited by capacity and endurance, UAVs often need to cooperate with ground vehicles or humans. This work considers a practical medical delivery problem in which multiple pharmacies share a fleet of vehicles to provide urgent medical delivery services to hospitals. To further improve its operational efficiency while reducing cost, a novel delivery mode is proposed, in which human couriers and UAVs collaboratively fulfill the medical delivery tasks. Considering the heterogeneity of the fleets, the time-sensitive nature of urgent orders, and constraints like vehicle capacities, this problem is modeled as the Multi-depot Pickup and Delivery Problem with Soft Deadlines (MPDPSD), and a heuristic-based method is proposed. Through extensive computational experiments, it is proved that the proposed method can provide feasible solutions with good performance for practical medical delivery service in a short time. In addition, the collaboration mode performs better than conventional human-only mode.

Original languageEnglish
Title of host publication2023 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1340-1345
Number of pages6
ISBN (Electronic)9798350323153
DOIs
Publication statusPublished - 2023
Event2023 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2023 - Singapore, Singapore
Duration: 18 Dec 202321 Dec 2023

Publication series

Name2023 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2023

Conference

Conference2023 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2023
Country/TerritorySingapore
CitySingapore
Period18/12/2321/12/23

Keywords

  • Logistics Optimization
  • Medical Delivery Service
  • Pickup and Delivery Problem
  • Soft Deadlines
  • Unmanned Aerial Vehicle

ASJC Scopus subject areas

  • Artificial Intelligence
  • Decision Sciences (miscellaneous)
  • Statistics, Probability and Uncertainty
  • Industrial and Manufacturing Engineering
  • Modelling and Simulation
  • Strategy and Management

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